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Evaluating the causal effect of a treatment or intervention on an outcome of interest is a fundamental statistical problem. This problem is pervasive across various disciplines, such as economics, political science, psychology, biomedical science, and numerous others. For instance, economists hope to examine the effect of enrolling in a job training program on the future earning.

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Causal Inference for a Discrete Treatment

  • 章节

  • 出版模式：

    开放获取

  • 发表日期：

    2026年

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  • Zheng Zhang,
  • Kun Zhang,
  • Xing Yan,
  • Songshan Yang,
  • Yuqian Zhang

摘要

Evaluating the causal effect of a treatment or intervention on an outcome of interest is a fundamental statistical problem. This problem is pervasive across various disciplines, such as economics, political science, psychology, biomedical science, and numerous others. For instance, economists hope to examine the effect of enrolling in a job training program on the future earning.